Data Integrity: TGA Expectations Stephen Hart Senior Inspector, - - PowerPoint PPT Presentation

Data Integrity: TGA Expectations

Stephen Hart Senior Inspector, Manufacturing Quality Branch, TGA PDA conference July 2015

Presentation Overview

• What is Data Integrity?
• Global/Australian/US FDA Environments
• Data Integrity General Examples
• Basic Data Integrity Expectations
• ALCOA Principles
• TGA Licensed Manufacturers Expectations
• Conclusions

1

What is data integrity?

• The extent to which all data are complete, consistent

and accurate throughout the data lifecycle

• From initial data generation and recording through

processing (including transformation or migration), use, retention, archiving, retrieval and destruction.

(MHRA Guidance March 2015)

2

Why so much interest now?- Global Environment

Manufacturer 1 Overwriting of electronic raw data until acceptable results were achieved OOS not initiated Falsification of data to support regulatory filings Stand alone GC systems without adequate controls Manufacturer 2 Falsification of batch records (re-writing clean records) Non-contemporaneous recording of lab data Recording of sample weights on scraps of paper Missing raw data Manufacturer 3 Unofficial testing of samples (trial samples) OOS results not investigated Retesting completed but not justified No restriction/protection of electronic data Manufacturer 4 Chromatographic software was not validated to ensure re- writing, deletion of data prohibited Manufacturer 5 IPQC performed without batch record present Unexplained ‘trial’ samples run before analysis Deletion of HPLC data -lack of data security Missing stability samples Manufacturer 6 Lack of records demonstrating who performed analysis Raw data not recorded contemporaneously nor by the performing analyst Failed injections of QC standards (SS) deleted, repeated and inserted into the analytical sequence without explanation.

3

US FDA Environment:

www.fda.gov.downloads/drugs/developmentapprovalprocess/smallbusinessassistance/UCM407991.pdf

4

Australian Environment: Inspection report

• DEFINITIONS
• Critical Deficiency
• A deficiency in a practice or process that has produced, or may result in, a significant risk of producing a

product that is harmful to the user. Also occurs when it is observed that the manufacturer has engaged in fraud, misrepresentation or falsification of products or data.

5

Data Integrity: General Examples

Need to know the difference between falsification and poor/bad GMP/practice

• Human errors

– data entered by mistake – ignorance (not being aware of regulatory requirements or poor training) – Wilfully (falsification or fraud with the intent to deceive)

• Selection of good or passing results to the exclusion or poor or failing results
• Unauthorised changes to data post acquisition

Ref: “Data Integrity” pharmauptoday@gmail.com 6

Data Integrity: General Examples

• Errors during transmission from one computer to another
• Changes due to software bugs or malware of which the user is unaware
• Hardware malfunctions
• Technology changes making an older item obsolete – old records may become unreadable or

inaccessible

7 Ref: “Data Integrity” pharmauptoday@gmail.com

Basic Data Integrity expectations – Manufacturing Principles

• PIC/S Guide PE009-8:

– Chapter 4 – Annex 11

• Australian Code GMP human blood, blood components, human

tissues and human cellular therapy products – Sections 400 – 415

• ISO 13485

– Sections 4.2.3, 4.2.4

8

Basic Data Integrity expectations

• Regulator responses

– MHRA notifications to industry: December 2013 & March 2015 – FDA – Health Canada

• Influencing factors:

– Organisational culture, risk awareness and leadership – QMS design of systems to comply with DI principles

• “ALCOA” principles

– Company processes for data review and system monitoring

9

Attributable

• Clearly

indicates who recorded the data or performed the activity

• Signed /

dated

• Who wrote it

/ when

Legible

• It must be

possible to read or interpret the data after it is recorded

• Permanent
• No

unexplained hieroglyphics

• Properly

corrected if necessary

Contemporaneous

• Data must be

recorded at the time it was generated

• Close

proximity to

• ccurrence

Original

• Data must be

preserved in its unaltered state

• If not, why

not

• Certified

copies

Accurate

• Data must

correctly reflect the action /

• bservation

made

• Data checked

where necessary

• Modifications

explained if not self- evident

ALCOA Principles

10

TGA Licensed Manufacturers Expectations

• Manufacturers should:

– Understand their vulnerabilities to DI issues

• Not just about your site –
• Contractors (outsourced activities)

– Assess risks relating to data integrity- QRM Approach

11

TGA Licensed Manufacturers Expectations

• Manufacturers should:

– Design systems to prevent DI issues

• Ensure the data is authentic and retrievable

– Train staff and encourage correct behaviours and practices

• Open communication
• Encourage feedback

– System for ongoing DI review

12

Conclusions

• GMP requirements already include provisions for DI- inspection report

definitions, PIC/S Guide to GMP for medicinal products

• Existing systems should be able to ensure data integrity, traceability and

reliability-Understand your vulnerabilities to DI issues – The inability of a manufacturer to detect and prevent poor data integrity practices = lack of quality system effectiveness

• QRM approach to prevent, detect and control potential risks

13

Conclusions continued

• Where data is generated and used to make manufacturing and quality

decisions, ensure it is trustworthy and reliable

• Increased regulator focus on DI
• Remember it’s the responsibility of the manufacturer to prevent and detect

data integrity vulnerabilities

14